In order to facilitate storage and transfer of imagery data, the imagery data must oftentimes be compressed. As such, various lossy compression techniques have been developed. For example, a number of lossy wavelet-based compression techniques utilizing wavelet transforms have emerged as promising alternatives to traditional spectral decompositions such as Fourier and cosine transforms. See, for example, G. Strang and T. Nguyen, Wavelets and Filter Banks, Welleslay-Cambridge Press, Welleslay Mass. (1996).
However, image data may sometimes include data values that are significantly different than the adjacent data values and are not representative of the underlying image. In regards to elevation data, such as that utilized by aircraft navigation programs, null posts are inserted in the image data to provide a default elevation for those locations for which actual elevation data is unavailable. In order to identify the null posts as a placeholder as opposed to an actual elevation value, null posts having an elevation value of −32,768 meters may be utilized since this elevation value otherwise never occurs. As another example, the image data representative of an image to be presented upon a computer monitor or other display, such as the image represented by a JPEG file may include a textual or graphical overlay that is defined by corresponding data values that differ significantly from the data values representative of the underlying image adjacent the textual or graphical overlay. In these instances, the lossy compression of the data values representative of the null posts, the textual or graphical overlays or other features that are distinct from the underlying image may cause distortion in the resulting image, i.e., the image following compression and then subsequent decompression. This distortion is due to quantization which may cause the data values representative of the null posts or graphical or textual overlays, for example, to deviate from their original value, thereby rendering it more difficult to properly identify each of these data values. For example, a data value representative of a null post may not be recognized as such a data value if its value has been perturbed from the pre-assigned value of −32,768. Additionally, the lossy compression of the data values representative of null posts, textual or graphical overlays or other features that are distinct from the underlying image may cause blurring and aliasing effects that cause the oftentimes extreme values of these data values to adversely effect the values of adjacent pixels which, therefore, disadvantageously alter the resulting decompressed image. As such, it would be desirable to provide a technique to permit more accurate reconstruction of image data following lossy wavelet-based compression even in instances in which the image data includes data values representative of a null post, an overlay or some other feature that is not included within the underlying image.
One technique for minimizing the distortion in the resulting images defines regions of interest that include those data values representative of null posts, overlays, or other features that differ from and are not a portion of the underlying image. Each region of interest may be compressed via a lossless compression technique in a manner distinct from the lossy wavelet-based compression to which the remainder of the image is subjected. While the resulting image will have less distortion, the use of lossless compression for the regions of interest reduces the amount of compression and therefore disadvantageously increases the size of the resulting image file. Accordingly, it would also be desirable to subject all of the image data to lossy wavelet-based compression so as to maintain relatively good compression performance while minimizing the distortion in the resulting image even in instances in which the image data includes null posts, overlays or other features that are not present in the underlying image.